Variable image (VI) print jobs are continually growing in terms of sophistication and complexity. Additions and deletions to VI print jobs are based on a growing number of conditions, such as, e.g., policy, a person's status, the company with which they are doing business (which may not be the company printing the reports), so it becomes important to check for correctness of the finished output product. Liabilities can be very large for an incorrect output. For example, a credit card company might send a person's bill to a wrong address, and perhaps repeat this for several million customers. Because of the increasing sophistication and the large volume, checking by hand becomes more and more difficult and tedious. Therefore, various methods of automating the process of checking have been developed. For example, checks can be scanned after printing, and an optical character recognition (OCR) process can be used for checking against a database for correctness. It would also be desirable, however, to check that the correct logo and other images have been printed, and that the correct paragraphs have been printed, etc. Every reasonable action must be taken to prevent mistakes.
This prevention of mistakes in VI print jobs applies not only to checks, but other documents as well. It applies anywhere that it is important to know that the correct images and text, such as amounts and account numbers, have been produced. Checking the accuracy of the output is of paramount importance because a specification of complex and lengthy variable image print jobs can involve complex interaction between data sources and can, therefore, lead to unexpected results. Errors in query logic can cause catastrophic information disclosure. For example, consider the impact of simply mailing credit card information to the wrong address for several thousand people. In current printing practice, operators check samples for correctness manually. It is not clear, however, that operators can or will catch all mistakes or that the sample set utilized for checking adequately exercises the query logic in order to reveal all problems. Therefore, there exists a need for improved methods for automatic review of variable imaging print jobs.